We place people at the centre of technological innovation. Our researchers study how humans interact with digital systems and use those insights to design better ones. From immersive virtual environments to AI-powered interfaces, from accessible devices to data-driven tools for health, our work spans the full spectrum of Human-Computer Interaction. We combine technical innovation with social science rigour, ensuring that the systems we build are not only functional, but fair, inclusive, and meaningful.
Our research spans three strengths across multidisciplinary research
Research on virtual, augmented, mixed, and extended reality explores immersive digital experiences that blend the virtual and physical worlds. The popularisation of VR and MR headsets has driven the need to understand how these technologies impact work and play, while opening entirely new ways of interacting with technology. Our work explores new devices and techniques for 3D interaction, novel interface paradigms for extended reality, and approaches for enabling remote users to collaborate in mixed reality environments.
Our research spans the full XR spectrum, from fully virtual environments to seamlessly blended physical-digital spaces. We design and evaluate novel input devices, interaction techniques, and collaborative systems, working with both commodity headsets and custom-built hardware. Recent work includes using novel AR display surfaces, enabling remote collaborators to collaborate over mixed reality, and developing tactile feedback systems that let users feel virtual objects.
This research advances how people work, learn, and collaborate in immersive environments. By developing new interaction techniques and collaborative tools for XR, we help organisations deploy these technologies more effectively, whether for remote teamwork, training, or creative work. Our findings inform the design of the next generation of XR devices and experiences, with applications across industries including healthcare, education, engineering, and the arts.
Professor Eduardo Velloso, Associate Professor Anusha Withana
Intelligent interfaces are transforming the way we interact with technology. Modern devices learn behavioural patterns, make intelligent recommendations, and perform informed actions accordingly. Our work develops and evaluates novel systems designed to understand users’ context and intuitively respond to each user's unique needs, enhancing how people use and connect with their devices.
Our research investigates how machine learning and AI can be embedded into everyday interfaces to make them more responsive, context-aware, and personalised. We study how interfaces can anticipate user intent, manage attention, and reduce cognitive load. We also explore human-AI collaboration as a creative tool, developing systems that assist users in tasks they might not otherwise attempt, such as generating humorous content.
Intelligent interfaces have the potential to make technology more intuitive and less demanding for everyone. By designing systems that adapt to individual users rather than requiring users to adapt to the system, our research contributes to more productive, less frustrating digital experiences. Our work on adaptive agents in augmented reality has direct implications for high-stakes environments, such as surgery, logistics, and education, where managing attention and cognitive load is critical.
Professor Eduardo Velloso, Professor Judy Kay, Associate Professor Anusha Withana, Dr Katy Gero, Dr Jonathan Kummerfeld
As AI agents become pervasive in the systems we use in everyday life, it becomes critical to understand how users perceive and react to their actions and behaviours. Our team draws on methods from the social sciences to explore how humans perceive, judge, collaborate with, and disagree with AI agents, with the goal of designing AI-powered interfaces that are trustworthy, effective, and human-centred.
Our research investigates the cognitive, social, and ethical dimensions of human-AI relationships. We study how AI shapes creative processes, including its role in supporting or constraining divergent thinking and creative writing, and how users form moral judgements about AI behaviour. We also examine fairness perceptions in AI systems, and how trust and collaboration between humans and machines can be fostered across high-stakes domains such as healthcare, education, and entertainment.
As AI becomes embedded in the tools people use every day, understanding how users relate to AI agents is essential for responsible design. Our research produces empirically grounded insights that help designers and developers build AI systems people can trust, question, and collaborate with effectively. Findings from our work directly inform the design of AI-powered tools in creative industries, education, and professional settings, domains where the stakes of getting human-AI interaction wrong are high.
Professor Eduardo Velloso, Professor Judy Kay, Professor Mary Lou Maher, Dr Zhanna Sarsenbayeva, Dr Katy Gero, Angie Zhang
As interactive technologies become deeply embedded in everyday life, questions of ethics, fairness, and governance become inseparable from their design. Our research examines how technology policies are formed, how ethical principles can be operationalised in system design, and how affected communities can meaningfully participate in shaping the rules that govern the technologies they use.
We draw on methods from HCI, social science, and legal scholarship to study algorithmic accountability, data ethics, AI governance, platform regulation, and the broader societal implications of emerging technologies. Our work centres the perspectives of those most affected by technological systems, including gig workers, knowledge workers, and creative practitioners, examining how they experience, contest, and seek to reshape the AI-driven systems in their professional and creative lives.
Technology policy and ethics research has direct consequences for how AI systems are governed and who benefits from them. Our work produces frameworks, guidelines, and empirical evidence that inform policy debates and design practice, helping organisations build AI systems that are accountable, transparent, and fair. By amplifying the voices of affected communities, our research contributes to a more equitable digital future where governance keeps pace with technological change.
Professor Eduardo Velloso, Professor Mary Lou Maher, Dr Zhanna Sarsenbayeva, Dr Katy Gero, Angie Zhang
We develop interactive devices using digital fabrication to create personalised interfaces tailored to individual users and contexts. These devices are complemented by computational design tools that enable users to design their own interfaces, democratising the creation of interactive hardware. Our work combines technical innovation with human-centred evaluation to rigorously validate fabrication strategies, design methods, and the resulting devices.
Our research pushes the boundaries of what interactive devices can be made of, how they are made, and where they can be worn or placed. We explore sustainable bio-based fabrication using myco-materials, develop ultra-thin on-skin interfaces that deliver tactile sensation through the skin, and create flexible epidermal sensors that detect subtle body movements. We also investigate spatial tactile feedback systems that allow users to physically feel and explore virtual geometry, bridging the physical and digital through the sense of touch.
Digital fabrication is transforming who can create interactive technology and what form that technology can take. Our research lowers the barriers to hardware creation, enabling individuals, clinicians, educators, and designers to build devices tailored to their specific needs. By advancing fabrication techniques and design tools, we contribute to a future where personalised, accessible, and sustainable interactive devices are within everyone's reach, with applications spanning healthcare, rehabilitation, education, and creative practice.
Associate Professor Anusha Withana
Designing accessible technology is essential to ensure that everyone, regardless of ability or disability, can fully participate in and benefit from the digital world. Our research explores the challenges of creating accessible technology, develops concrete design guidelines, and creates technological solutions that can be used by people with diverse abilities. We take a participatory approach, involving people with disabilities and their caregivers as co-designers rather than passive research subjects.
Our work spans the full arc of accessible technology research, from co-designing with end-users to building novel assistive devices. We leverage digital fabrication to create low-cost, customisable solutions such as 3D-printed EEG electrodes and gesture recognition sensors. We partner with families of children with disabilities to co-design playful, empowering technologies. And we critically evaluate the accessibility tooling ecosystem itself, examining how well existing tools support designers in embedding accessibility from the earliest stages of development.
Accessible technology research has direct and immediate consequences for people's lives, enabling participation, independence, and dignity for individuals who might otherwise be excluded from the digital world. Our research produces both practical tools and evidence-based guidelines that help industry and government meet their accessibility obligations and go beyond mere compliance. By taking a participatory, community-centred approach, we ensure our work reflects the real needs and preferences of the people it is designed to serve.
Associate Professor Anusha Withana, Dr Zhanna Sarsenbayeva, Professor Judy Kay
In our increasingly digital lives, the systems we use every day capture vast amounts of data about us, from steps walked and sleep quality, to heart rate and activity patterns. Our research aims to create systems that help people harness this data meaningfully, moving beyond raw numbers toward genuine insight and behaviour change. A key focus is health and wellness, where better understanding of data from wearables such as smartwatches and rings can support more informed, personalised decisions.
Our work investigates how people engage with self-tracking data over the long term, including the challenges of sustained engagement, evolving user needs, and avoiding data overload. We design interfaces that surface new insights from longitudinal personal data, helping users recognise patterns they would otherwise miss. We also scale personal informatics to the population level, analysing large-scale activity data to understand how communities and nations move and behave, and what that tells us about public health.
Personal informatics research has the potential to transform how individuals manage their health and how organisations design public health interventions. By helping people make sense of their own data, our work supports healthier behaviours, more informed clinical conversations, and greater personal agency over health outcomes. At the population scale, our research provides insights that can inform urban planning, workplace wellness programmes, and national health policy, turning the data already generated by everyday devices into a resource for collective benefit.
Professor Judy Kay, Professor Irena Koprinska
We advance the theoretical and methodological foundations of Human-Computer Interaction as a discipline — not just applying methods, but critically examining and improving them. Our work champions rigorous study design and pushes for higher standards in how HCI research is conducted, analysed, and reported. We contribute to the evolution of HCI as a mature scientific discipline, fostering innovation in both theory and method.
Our research spans statistical practice, theory-building, and measurement. We advocate for more appropriate statistical approaches in HCI, including the adoption of ordinal regression for the kinds of data HCI researchers routinely collect. We develop causal modelling as a tool for theory-building, moving the field toward stronger and more falsifiable theoretical claims. We critically evaluate established measurement practices — including physiological sensing methods such as electrodermal activity — and set methodological standards for specialised areas of HCI research such as accessibility and motor impairment studies.
Methodology research has a multiplier effect across the entire discipline — better methods mean stronger findings, more reliable conclusions, and more cumulative scientific progress. Our work directly improves the quality of HCI research conducted worldwide by providing researchers with better tools, frameworks, and standards. By advocating for more rigorous statistical and theoretical practices, we help the field produce knowledge that is more trustworthy, more replicable, and more useful to the designers, engineers, and policymakers who rely on HCI research to inform their decisions.
Professor Eduardo Velloso, Dr Zhanna Sarsenbayeva
Making sense of large, complex datasets is one of the defining challenges of our data-rich age. Our research develops algorithms, techniques, and interactive systems that transform complex relational data into clear, human-readable visual representations. At the heart of this work is graph drawing — the science of producing intelligible pictures of networks — combined with visual analytics tools that help people discover hidden structure, patterns, and insights in data too large and complex to comprehend any other way.
Our research group, one of the world's leading centres for graph drawing and information visualisation, tackles problems at every scale — from the mathematical foundations of how graphs can be drawn without visual clutter, to scalable algorithms capable of visualising networks with billions of nodes. We develop new layout algorithms, 3D and multi-plane graph embeddings, and interactive navigation techniques that preserve the user's mental map as data changes dynamically. Application domains include social network analysis, biological network visualisation, software architecture, fraud detection, and counter-terrorism.
The ability to visualise complex networks has profound practical consequences across science, industry, and government. Our graph drawing algorithms underpin visualisation software used in data mining, bioinformatics, market surveillance, and security analysis. By developing scalable visual analytics methods for extreme-scale networks, our research enables analysts — in fields from public health to intelligence — to extract new knowledge from datasets that would otherwise be impenetrable. This work directly supports Australia's capacity to make sense of the growing complexity of digital, biological, and social systems.
Professor Seokhee Hong, Professor Peter Eades, Professor Masa Takatsuka
